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description Publicationkeyboard_double_arrow_right Article , Research 2024 SwitzerlandPublisher:Frontiers Media SA Authors: Dorian Quelle; Dorian Quelle; Alexandre Bovet; Alexandre Bovet;Dorian Quelle; Dorian Quelle; Alexandre Bovet; Alexandre Bovet;Automated fact-checking, using machine learning to verify claims, has grown vital as misinformation spreads beyond human fact-checking capacity. Large language models (LLMs) like GPT-4 are increasingly trusted to write academic papers, lawsuits, and news articles and to verify information, emphasizing their role in discerning truth from falsehood and the importance of being able to verify their outputs. Understanding the capacities and limitations of LLMs in fact-checking tasks is therefore essential for ensuring the health of our information ecosystem. Here, we evaluate the use of LLM agents in fact-checking by having them phrase queries, retrieve contextual data, and make decisions. Importantly, in our framework, agents explain their reasoning and cite the relevant sources from the retrieved context. Our results show the enhanced prowess of LLMs when equipped with contextual information. GPT-4 outperforms GPT-3, but accuracy varies based on query language and claim veracity. While LLMs show promise in fact-checking, caution is essential due to inconsistent accuracy. Our investigation calls for further research, fostering a deeper comprehension of when agents succeed and when they fail.
Frontiers in Artific... arrow_drop_down Frontiers in Artificial IntelligenceArticle . 2024 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3389/frai.2024.1341697&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Frontiers in Artific... arrow_drop_down Frontiers in Artificial IntelligenceArticle . 2024 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3389/frai.2024.1341697&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SwitzerlandPublisher:Elsevier BV Authors: Räz, Tim;Räz, Tim;The interpretability of ML models is important, but it is not clear what it amounts to. So far, most philosophers have discussed the lack of interpretability of black-box models such as neural networks, and methods such as explainable AI that aim to make these models more transparent. The goal of this paper is to clarify the nature of interpretability by focussing on the other end of the 'interpretability spectrum'. The reasons why some models, linear models and decision trees, are highly interpretable will be examined, and also how more general models, MARS and GAM, retain some degree of interpretability. I find that while there is heterogeneity in how we gain interpretability, what interpretability is in particular cases can be explicated in a clear manner. Comment: 22 pages, 4 figures
https://doi.org/10.4... arrow_drop_down Studies in History and Philosophy of Science Part AArticle . 2024 . Peer-reviewedLicense: CC BYData sources: CrossrefBern Open Repository and Information System (BORIS)Article . 2024 . Peer-reviewedData sources: Bern Open Repository and Information System (BORIS)arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.shpsa.2023.12.007&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert https://doi.org/10.4... arrow_drop_down Studies in History and Philosophy of Science Part AArticle . 2024 . Peer-reviewedLicense: CC BYData sources: CrossrefBern Open Repository and Information System (BORIS)Article . 2024 . Peer-reviewedData sources: Bern Open Repository and Information System (BORIS)arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.shpsa.2023.12.007&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:Elsevier BV Authors: Akyildirim, Erdinc; Gambara, Matteo; Teichmann, Josef; Zhou, Syang;Akyildirim, Erdinc; Gambara, Matteo; Teichmann, Josef; Zhou, Syang;We present convincing empirical results on the application of Randomized Signature Methods for non-linear, non-parametric drift estimation for a multi-variate financial market. Even though drift estimation is notoriously ill defined due to small signal to noise ratio, one can still try to learn optimal non-linear maps from data to future returns for the purposes of portfolio optimization. Randomized Signatures, in contrast to classical signatures, allow for high dimensional market dimension and provide features on the same scale. We do not contribute to the theory of Randomized Signatures here, but rather present our empirical findings on portfolio selection in real world settings including real market data and transaction costs.
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4676478&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4676478&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:Elsevier BV Funded by:SNSF | Automatic recognition of ...SNSF| Automatic recognition of general unconstrained handwritten textSchimanski, Tobias; Senni, Chiara Colesanti; Gostlow, Glen; Ni, Jingwei; Yu, Tingyu; Leippold, Markus;Nature is an amorphous concept. Yet, it is essential for the planet's well-being to understand how the economy interacts with it. To address the growing demand for information on corporate nature disclosure, we provide datasets and classifiers to detect nature communication by companies. We ground our approach in the guidelines of the Taskforce on Nature-related Financial Disclosures (TNFD). Particularly, we focus on the specific dimensions of water, forest, and biodiversity. For each dimension, we create an expert-annotated dataset with 2,200 text samples and train classifier models. Furthermore, we show that nature communication is more prevalent in hotspot areas and directly effected industries like agriculture and utilities. Our approach is the first to respond to calls to assess corporate nature communication on a large scale.
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4665715&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4665715&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Research , Article , Other literature type 2024Embargo end date: 08 Mar 2024 Switzerland EnglishPublisher:ETH Zurich Jiang, Wenqi; Zhang, Shuai; id_orcid0000-0002-7866-4611; Han, Boran; Wang, Jie; Wang, Bernie; Kraska, Tim;handle: 20.500.11850/663487
Retrieval-augmented generation (RAG) can enhance the generation quality of large language models (LLMs) by incorporating external token databases. However, retrievals from large databases can constitute a substantial portion of the overall generation time, particularly when retrievals are periodically performed to align the retrieved content with the latest states of generation. In this paper, we introduce PipeRAG, a novel algorithm-system co-design approach to reduce generation latency and enhance generation quality. PipeRAG integrates (1) pipeline parallelism to enable concurrent retrieval and generation processes, (2) flexible retrieval intervals to maximize the efficiency of pipeline parallelism, and (3) a performance model to automatically balance retrieval quality and latency based on the generation states and underlying hardware. Our evaluation shows that, by combining the three aforementioned methods, PipeRAG achieves up to 2.6$\times$ speedup in end-to-end generation latency while improving generation quality. These promising results showcase the effectiveness of co-designing algorithms with underlying systems, paving the way for the adoption of PipeRAG in future RAG systems.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3929/ethz-b-000663487&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3929/ethz-b-000663487&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SwitzerlandPublisher:Elsevier BV Authors: Arvanitis, Stelios; Scaillet, Olivier; Topaloglou, Nikolas;Arvanitis, Stelios; Scaillet, Olivier; Topaloglou, Nikolas;We develop and implement methods for determining whether relaxing sparsity con- straints on portfolios improves the investment opportunity set for risk-averse investors. We formulate a new estimation procedure for sparse second-order stochastic spanning based on a greedy algorithm and Linear Programming. We show the optimal recovery of the sparse solution asymptotically whether spanning holds or not. From large equity datasets, we estimate the expected utility loss due to possible under-diversification, and find that there is no benefit from expanding a sparse opportunity set beyond 45 assets. The optimal sparse portfolio invests in 10 industry sectors and cuts tail risk when compared to a sparse mean-variance portfolio. On a rolling-window basis, the number of assets shrinks to 25 assets in crisis periods, while standard factor models cannot explain the performance of the sparse portfolios
Archive ouverte UNIG... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2024Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4713517&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Archive ouverte UNIG... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2024Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4713517&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Conference object 2023 SwitzerlandPublisher:IEEE Funded by:EC | INODEEC| INODEAuthors: Kosten, Catherine; Cudré-Mauroux, Philippe; Stockinger, Kurt;Kosten, Catherine; Cudré-Mauroux, Philippe; Stockinger, Kurt;With the recent spike in the number and availability of Large Language Models (LLMs), it has become increasingly important to provide large and realistic benchmarks for evaluating Knowledge Graph Question Answering (KGQA) systems. So far the majority of benchmarks rely on pattern-based SPARQL query generation approaches. The subsequent natural language (NL) question generation is conducted through crowdsourcing or other automated methods, such as rule-based paraphrasing or NL question templates. Although some of these datasets are of considerable size, their pitfall lies in their pattern-based generation approaches, which do not always generalize well to the vague and linguistically diverse questions asked by humans in real-world contexts. In this paper, we introduce Spider4SPARQL - a new SPARQL benchmark dataset featuring 9,693 previously existing manually generated NL questions and 4,721 unique, novel, and complex SPARQL queries of varying complexity. In addition to the NL/SPARQL pairs, we also provide their corresponding 166 knowledge graphs and ontologies, which cover 138 different domains. Our complex benchmark enables novel ways of evaluating the strengths and weaknesses of modern KGQA systems. We evaluate the system with state-of-the-art KGQA systems as well as LLMs, which achieve only up to 45\% execution accuracy, demonstrating that Spider4SPARQL is a challenging benchmark for future research. Comment: 10 pages, 5 figures, accepted at IEEE BigData Conference 2023, 8th IEEE Special Session on Machine Learning on Big Data (MLBD 2023)
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/bigdat...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/bigdata59044.2023.10386182&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/bigdat...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/bigdata59044.2023.10386182&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 IrelandPublisher:University Library J. C. Senckenberg Publicly fundedAuthors: Louis Mahon; Carl Vogel;Louis Mahon; Carl Vogel;handle: 2262/104231
This paper presents FASTFOOD, a rule-based natural language generation (NLG) program for cooking recipes. We consider the representation of cooking recipes as discourse representation, because the meaning of each sentence needs to consider the context of the others. Our discourse representation system is based on states of affairs and transtions between states of affairs, and does not use discourse referents. Recipes are generated by using an automated theorem-proving procedure to select the ingredients and instructions, with ingredients corresponding to axioms and instructions to implications. FASTFOOD also contains a temporal optimization module which can rearrange the recipe to make it more time efficient for the user, e.g. the recipe specifies to chop the vegetables while the rice is boiling. The system is described in detail, including the decision to forgo discourse referents and how plausible representations of nouns and verbs emerge purely as a by-product of the practical requirements of efficiently representing recipe content. A comparison is then made with existing recipe generation systems, NLG systems more generally, and automated theorem provers.
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.21248/jlcl....Article . 2023 . Peer-reviewedLicense: CC BY SAData sources: CrossrefTrinity's Access to Research ArchiveArticle . 2023 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21248/jlcl.36.2023.233&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.21248/jlcl....Article . 2023 . Peer-reviewedLicense: CC BY SAData sources: CrossrefTrinity's Access to Research ArchiveArticle . 2023 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21248/jlcl.36.2023.233&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 United KingdomPublisher:IOP Publishing Li, Haiwei; Zhao, Yongling; Bardhan, Ronita; Kubilay, Aytac; Derome, Dominique; Carmeliet, Jan;Nowadays, cities are frequently exposed to heatwaves, worsening the outdoor thermal comfort and increasing cooling energy demand in summer. Urban forestry is seen as one of the viable and preferable solutions to combating extreme heat events and urban heat island (UHI) in times of climate change. While many cities have initiated tree-planting programmes in recent years, the evolving impact of trees on street microclimate, in a time span of up to several decades, remains unclear. We investigate the cooling effects of linden trees in five groups, i.e., 10-20, 20-30, 30-40, 40-60, and 60-100 years old. The leaf area index (LAI) and leaf area density (LAD) vary nonlinearly as the trees grow, peaking at different ages. Computational fluid dynamics (CFD) simulations solving microclimate are performed for an idealized street canyon with trees of varied age groups. Turbulent airflow, heat and moisture transport, shortwave and longwave radiation, shading and transpiration are fully coupled and solved in OpenFOAM. The meteorological data, including air temperature, wind speed, moisture, and shortwave radiation of the heatwave in Zurich (June 2019), are applied as boundary conditions. The results show that young trees in the age group of 10-20 years old provide little heat mitigation at the pedestrian level in an extreme heat event. Optimal heat mitigation by trees is observed for the group of 30-60 years old trees. Finally, the potential impact of growing trees as a heat mitigation measure on air ventilation is evaluated. Comment: 4 figures, 8 pages
Journal of Physics :... arrow_drop_down Journal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2654/1/012145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Journal of Physics :... arrow_drop_down Journal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2654/1/012145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023 Germany, SwitzerlandPublisher:Association for Computing Machinery (ACM) Hu, Xuke; Zhou, Zhiyong; Li, Hao; Hu, Yingjie; Gu, Fuqiang; Kersten, Jens; Fan, Hongchao; Klan, Friederike;A vast amount of location information exists in unstructured texts, such as social media posts, news stories, scientific articles, web pages, travel blogs, and historical archives. Geoparsing refers to the process of recognizing location references from texts and identifying their geospatial representations. While geoparsing can benefit many domains, a summary of the specific applications is still missing. Further, there lacks a comprehensive review and comparison of existing approaches for location reference recognition, which is the first and a core step of geoparsing. To fill these research gaps, this review first summarizes seven typical application domains of geoparsing: geographic information retrieval, disaster management, disease surveillance, traffic management, spatial humanities, tourism management, and crime management. We then review existing approaches for location reference recognition by categorizing these approaches into four groups based on their underlying functional principle: rule-based, gazetteer matching-based, statistical learning-based, and hybrid approaches. Next, we thoroughly evaluate the correctness and computational efficiency of the 27 most widely used approaches for location reference recognition based on 26 public datasets with different types of texts (e.g., social media posts and news stories) containing 39,736 location references across the world. Results from this thorough evaluation can help inform future methodological developments for location reference recognition, and can help guide the selection of proper approaches based on application needs. 35 pages, 11 figures
Zurich Open Reposito... arrow_drop_down Zurich Open Repository and ArchiveArticle . 2024License: CC BYData sources: Zurich Open Repository and ArchiveDLR publication server; ACM Computing SurveysArticle . 2022 . 2023 . Peer-reviewedarXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3625819&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!more_vert Zurich Open Reposito... arrow_drop_down Zurich Open Repository and ArchiveArticle . 2024License: CC BYData sources: Zurich Open Repository and ArchiveDLR publication server; ACM Computing SurveysArticle . 2022 . 2023 . Peer-reviewedarXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3625819&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Article , Research 2024 SwitzerlandPublisher:Frontiers Media SA Authors: Dorian Quelle; Dorian Quelle; Alexandre Bovet; Alexandre Bovet;Dorian Quelle; Dorian Quelle; Alexandre Bovet; Alexandre Bovet;Automated fact-checking, using machine learning to verify claims, has grown vital as misinformation spreads beyond human fact-checking capacity. Large language models (LLMs) like GPT-4 are increasingly trusted to write academic papers, lawsuits, and news articles and to verify information, emphasizing their role in discerning truth from falsehood and the importance of being able to verify their outputs. Understanding the capacities and limitations of LLMs in fact-checking tasks is therefore essential for ensuring the health of our information ecosystem. Here, we evaluate the use of LLM agents in fact-checking by having them phrase queries, retrieve contextual data, and make decisions. Importantly, in our framework, agents explain their reasoning and cite the relevant sources from the retrieved context. Our results show the enhanced prowess of LLMs when equipped with contextual information. GPT-4 outperforms GPT-3, but accuracy varies based on query language and claim veracity. While LLMs show promise in fact-checking, caution is essential due to inconsistent accuracy. Our investigation calls for further research, fostering a deeper comprehension of when agents succeed and when they fail.
Frontiers in Artific... arrow_drop_down Frontiers in Artificial IntelligenceArticle . 2024 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3389/frai.2024.1341697&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Frontiers in Artific... arrow_drop_down Frontiers in Artificial IntelligenceArticle . 2024 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3389/frai.2024.1341697&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SwitzerlandPublisher:Elsevier BV Authors: Räz, Tim;Räz, Tim;The interpretability of ML models is important, but it is not clear what it amounts to. So far, most philosophers have discussed the lack of interpretability of black-box models such as neural networks, and methods such as explainable AI that aim to make these models more transparent. The goal of this paper is to clarify the nature of interpretability by focussing on the other end of the 'interpretability spectrum'. The reasons why some models, linear models and decision trees, are highly interpretable will be examined, and also how more general models, MARS and GAM, retain some degree of interpretability. I find that while there is heterogeneity in how we gain interpretability, what interpretability is in particular cases can be explicated in a clear manner. Comment: 22 pages, 4 figures
https://doi.org/10.4... arrow_drop_down Studies in History and Philosophy of Science Part AArticle . 2024 . Peer-reviewedLicense: CC BYData sources: CrossrefBern Open Repository and Information System (BORIS)Article . 2024 . Peer-reviewedData sources: Bern Open Repository and Information System (BORIS)arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.shpsa.2023.12.007&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert https://doi.org/10.4... arrow_drop_down Studies in History and Philosophy of Science Part AArticle . 2024 . Peer-reviewedLicense: CC BYData sources: CrossrefBern Open Repository and Information System (BORIS)Article . 2024 . Peer-reviewedData sources: Bern Open Repository and Information System (BORIS)arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.shpsa.2023.12.007&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:Elsevier BV Authors: Akyildirim, Erdinc; Gambara, Matteo; Teichmann, Josef; Zhou, Syang;Akyildirim, Erdinc; Gambara, Matteo; Teichmann, Josef; Zhou, Syang;We present convincing empirical results on the application of Randomized Signature Methods for non-linear, non-parametric drift estimation for a multi-variate financial market. Even though drift estimation is notoriously ill defined due to small signal to noise ratio, one can still try to learn optimal non-linear maps from data to future returns for the purposes of portfolio optimization. Randomized Signatures, in contrast to classical signatures, allow for high dimensional market dimension and provide features on the same scale. We do not contribute to the theory of Randomized Signatures here, but rather present our empirical findings on portfolio selection in real world settings including real market data and transaction costs.
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4676478&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4676478&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024Publisher:Elsevier BV Funded by:SNSF | Automatic recognition of ...SNSF| Automatic recognition of general unconstrained handwritten textSchimanski, Tobias; Senni, Chiara Colesanti; Gostlow, Glen; Ni, Jingwei; Yu, Tingyu; Leippold, Markus;Nature is an amorphous concept. Yet, it is essential for the planet's well-being to understand how the economy interacts with it. To address the growing demand for information on corporate nature disclosure, we provide datasets and classifiers to detect nature communication by companies. We ground our approach in the guidelines of the Taskforce on Nature-related Financial Disclosures (TNFD). Particularly, we focus on the specific dimensions of water, forest, and biodiversity. For each dimension, we create an expert-annotated dataset with 2,200 text samples and train classifier models. Furthermore, we show that nature communication is more prevalent in hotspot areas and directly effected industries like agriculture and utilities. Our approach is the first to respond to calls to assess corporate nature communication on a large scale.
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4665715&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4665715&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Research , Article , Other literature type 2024Embargo end date: 08 Mar 2024 Switzerland EnglishPublisher:ETH Zurich Jiang, Wenqi; Zhang, Shuai; id_orcid0000-0002-7866-4611; Han, Boran; Wang, Jie; Wang, Bernie; Kraska, Tim;handle: 20.500.11850/663487
Retrieval-augmented generation (RAG) can enhance the generation quality of large language models (LLMs) by incorporating external token databases. However, retrievals from large databases can constitute a substantial portion of the overall generation time, particularly when retrievals are periodically performed to align the retrieved content with the latest states of generation. In this paper, we introduce PipeRAG, a novel algorithm-system co-design approach to reduce generation latency and enhance generation quality. PipeRAG integrates (1) pipeline parallelism to enable concurrent retrieval and generation processes, (2) flexible retrieval intervals to maximize the efficiency of pipeline parallelism, and (3) a performance model to automatically balance retrieval quality and latency based on the generation states and underlying hardware. Our evaluation shows that, by combining the three aforementioned methods, PipeRAG achieves up to 2.6$\times$ speedup in end-to-end generation latency while improving generation quality. These promising results showcase the effectiveness of co-designing algorithms with underlying systems, paving the way for the adoption of PipeRAG in future RAG systems.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3929/ethz-b-000663487&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3929/ethz-b-000663487&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2024 SwitzerlandPublisher:Elsevier BV Authors: Arvanitis, Stelios; Scaillet, Olivier; Topaloglou, Nikolas;Arvanitis, Stelios; Scaillet, Olivier; Topaloglou, Nikolas;We develop and implement methods for determining whether relaxing sparsity con- straints on portfolios improves the investment opportunity set for risk-averse investors. We formulate a new estimation procedure for sparse second-order stochastic spanning based on a greedy algorithm and Linear Programming. We show the optimal recovery of the sparse solution asymptotically whether spanning holds or not. From large equity datasets, we estimate the expected utility loss due to possible under-diversification, and find that there is no benefit from expanding a sparse opportunity set beyond 45 assets. The optimal sparse portfolio invests in 10 industry sectors and cuts tail risk when compared to a sparse mean-variance portfolio. On a rolling-window basis, the number of assets shrinks to 25 assets in crisis periods, while standard factor models cannot explain the performance of the sparse portfolios
Archive ouverte UNIG... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2024Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4713517&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Archive ouverte UNIG... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2024Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2139/ssrn.4713517&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Conference object 2023 SwitzerlandPublisher:IEEE Funded by:EC | INODEEC| INODEAuthors: Kosten, Catherine; Cudré-Mauroux, Philippe; Stockinger, Kurt;Kosten, Catherine; Cudré-Mauroux, Philippe; Stockinger, Kurt;With the recent spike in the number and availability of Large Language Models (LLMs), it has become increasingly important to provide large and realistic benchmarks for evaluating Knowledge Graph Question Answering (KGQA) systems. So far the majority of benchmarks rely on pattern-based SPARQL query generation approaches. The subsequent natural language (NL) question generation is conducted through crowdsourcing or other automated methods, such as rule-based paraphrasing or NL question templates. Although some of these datasets are of considerable size, their pitfall lies in their pattern-based generation approaches, which do not always generalize well to the vague and linguistically diverse questions asked by humans in real-world contexts. In this paper, we introduce Spider4SPARQL - a new SPARQL benchmark dataset featuring 9,693 previously existing manually generated NL questions and 4,721 unique, novel, and complex SPARQL queries of varying complexity. In addition to the NL/SPARQL pairs, we also provide their corresponding 166 knowledge graphs and ontologies, which cover 138 different domains. Our complex benchmark enables novel ways of evaluating the strengths and weaknesses of modern KGQA systems. We evaluate the system with state-of-the-art KGQA systems as well as LLMs, which achieve only up to 45\% execution accuracy, demonstrating that Spider4SPARQL is a challenging benchmark for future research. Comment: 10 pages, 5 figures, accepted at IEEE BigData Conference 2023, 8th IEEE Special Session on Machine Learning on Big Data (MLBD 2023)
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/bigdat...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/bigdata59044.2023.10386182&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archivehttps://doi.org/10.1109/bigdat...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/bigdata59044.2023.10386182&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 IrelandPublisher:University Library J. C. Senckenberg Publicly fundedAuthors: Louis Mahon; Carl Vogel;Louis Mahon; Carl Vogel;handle: 2262/104231
This paper presents FASTFOOD, a rule-based natural language generation (NLG) program for cooking recipes. We consider the representation of cooking recipes as discourse representation, because the meaning of each sentence needs to consider the context of the others. Our discourse representation system is based on states of affairs and transtions between states of affairs, and does not use discourse referents. Recipes are generated by using an automated theorem-proving procedure to select the ingredients and instructions, with ingredients corresponding to axioms and instructions to implications. FASTFOOD also contains a temporal optimization module which can rearrange the recipe to make it more time efficient for the user, e.g. the recipe specifies to chop the vegetables while the rice is boiling. The system is described in detail, including the decision to forgo discourse referents and how plausible representations of nouns and verbs emerge purely as a by-product of the practical requirements of efficiently representing recipe content. A comparison is then made with existing recipe generation systems, NLG systems more generally, and automated theorem provers.
arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.21248/jlcl....Article . 2023 . Peer-reviewedLicense: CC BY SAData sources: CrossrefTrinity's Access to Research ArchiveArticle . 2023 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21248/jlcl.36.2023.233&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down arXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archivehttps://doi.org/10.21248/jlcl....Article . 2023 . Peer-reviewedLicense: CC BY SAData sources: CrossrefTrinity's Access to Research ArchiveArticle . 2023 . Peer-reviewedData sources: Trinity's Access to Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.21248/jlcl.36.2023.233&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 United KingdomPublisher:IOP Publishing Li, Haiwei; Zhao, Yongling; Bardhan, Ronita; Kubilay, Aytac; Derome, Dominique; Carmeliet, Jan;Nowadays, cities are frequently exposed to heatwaves, worsening the outdoor thermal comfort and increasing cooling energy demand in summer. Urban forestry is seen as one of the viable and preferable solutions to combating extreme heat events and urban heat island (UHI) in times of climate change. While many cities have initiated tree-planting programmes in recent years, the evolving impact of trees on street microclimate, in a time span of up to several decades, remains unclear. We investigate the cooling effects of linden trees in five groups, i.e., 10-20, 20-30, 30-40, 40-60, and 60-100 years old. The leaf area index (LAI) and leaf area density (LAD) vary nonlinearly as the trees grow, peaking at different ages. Computational fluid dynamics (CFD) simulations solving microclimate are performed for an idealized street canyon with trees of varied age groups. Turbulent airflow, heat and moisture transport, shortwave and longwave radiation, shading and transpiration are fully coupled and solved in OpenFOAM. The meteorological data, including air temperature, wind speed, moisture, and shortwave radiation of the heatwave in Zurich (June 2019), are applied as boundary conditions. The results show that young trees in the age group of 10-20 years old provide little heat mitigation at the pedestrian level in an extreme heat event. Optimal heat mitigation by trees is observed for the group of 30-60 years old trees. Finally, the potential impact of growing trees as a heat mitigation measure on air ventilation is evaluated. Comment: 4 figures, 8 pages
Journal of Physics :... arrow_drop_down Journal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2654/1/012145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Journal of Physics :... arrow_drop_down Journal of Physics : Conference SeriesArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefarXiv.org e-Print ArchiveOther literature type . Preprint . 2023Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1088/1742-6596/2654/1/012145&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023 Germany, SwitzerlandPublisher:Association for Computing Machinery (ACM) Hu, Xuke; Zhou, Zhiyong; Li, Hao; Hu, Yingjie; Gu, Fuqiang; Kersten, Jens; Fan, Hongchao; Klan, Friederike;A vast amount of location information exists in unstructured texts, such as social media posts, news stories, scientific articles, web pages, travel blogs, and historical archives. Geoparsing refers to the process of recognizing location references from texts and identifying their geospatial representations. While geoparsing can benefit many domains, a summary of the specific applications is still missing. Further, there lacks a comprehensive review and comparison of existing approaches for location reference recognition, which is the first and a core step of geoparsing. To fill these research gaps, this review first summarizes seven typical application domains of geoparsing: geographic information retrieval, disaster management, disease surveillance, traffic management, spatial humanities, tourism management, and crime management. We then review existing approaches for location reference recognition by categorizing these approaches into four groups based on their underlying functional principle: rule-based, gazetteer matching-based, statistical learning-based, and hybrid approaches. Next, we thoroughly evaluate the correctness and computational efficiency of the 27 most widely used approaches for location reference recognition based on 26 public datasets with different types of texts (e.g., social media posts and news stories) containing 39,736 location references across the world. Results from this thorough evaluation can help inform future methodological developments for location reference recognition, and can help guide the selection of proper approaches based on application needs. 35 pages, 11 figures
Zurich Open Reposito... arrow_drop_down Zurich Open Repository and ArchiveArticle . 2024License: CC BYData sources: Zurich Open Repository and ArchiveDLR publication server; ACM Computing SurveysArticle . 2022 . 2023 . Peer-reviewedarXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3625819&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!more_vert Zurich Open Reposito... arrow_drop_down Zurich Open Repository and ArchiveArticle . 2024License: CC BYData sources: Zurich Open Repository and ArchiveDLR publication server; ACM Computing SurveysArticle . 2022 . 2023 . Peer-reviewedarXiv.org e-Print ArchiveOther literature type . Preprint . 2022Data sources: arXiv.org e-Print Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3625819&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu